AI Article Synopsis
- Bitter peptides are tiny pieces of proteins that can improve the taste of food and have health benefits, like helping with blood pressure and diabetes.
- The review talks about where these bitter peptides come from and how they function in our taste buds.
- It also highlights the use of computer technology to help identify and study these peptides better, aiming to create more useful applications in the future.
Article Abstract
Bitter peptides are small molecular peptides produced by the hydrolysis of proteins under acidic, alkaline, or enzymatic conditions. These peptides can enhance food flavor and offer various health benefits, with attributes such as antihypertensive, antidiabetic, antioxidant, antibacterial, and immune-regulating properties. They show significant potential in the development of functional foods and the prevention and treatment of diseases. This review introduces the diverse sources of bitter peptides and discusses the mechanisms of bitterness generation and their physiological functions in the taste system. Additionally, it emphasizes the application of bioinformatics in bitter peptide research, including the establishment and improvement of bitter peptide databases, the use of quantitative structure-activity relationship (QSAR) models to predict bitterness thresholds, and the latest advancements in classification prediction models built using machine learning and deep learning algorithms for bitter peptide identification. Future research directions include enhancing databases, diversifying models, and applying generative models to advance bitter peptide research towards deepening and discovering more practical applications.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11432553 | PMC |
| http://dx.doi.org/10.3390/ijms25189844 | DOI Listing |
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